In this course, you’ll learn about the fundamentals of trading, including the concept of trend, returns, stop-loss, and volatility. You will learn how to identify the profit source and structure of basic quantitative trading strategies. This course will help you gauge how well the model generalizes its learning, explain the differences between regression and forecasting, and identify the steps needed to create development and implementation backtesters. By the end of the course, you will be able to use Google Cloud Platform to build basic machine learning models in Jupyter Notebooks.
This course is part of the Machine Learning for Trading Specialization
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About this Course
Familiarization with basic concepts in Machine Learning and Financial Markets; advanced competency in Python Programming.
Could your company benefit from training employees on in-demand skills?
Try Coursera for BusinessWhat you will learn
Understand the fundamentals of trading, including the concepts of trend, returns, stop-loss, and volatility.
Define quantitative trading and the main types of quantitative trading strategies.
Understand the basic steps in exchange arbitrage, statistical arbitrage, and index arbitrage.
Understand the application of machine learning to financial use cases.
Skills you will gain
- Finance
- Trading
- Investment
- Machine Learning applied to Finance
Familiarization with basic concepts in Machine Learning and Financial Markets; advanced competency in Python Programming.
Could your company benefit from training employees on in-demand skills?
Try Coursera for BusinessSyllabus - What you will learn from this course
Introduction to Trading with Machine Learning on Google Cloud
Supervised Learning with BigQuery ML
Time Series and ARIMA Modeling
Introduction to Neural Networks and Deep Learning
Reviews
- 5 stars44.61%
- 4 stars30%
- 3 stars14.35%
- 2 stars4.35%
- 1 star6.66%
TOP REVIEWS FROM INTRODUCTION TO TRADING, MACHINE LEARNING & GCP
Good introduction to quant theory and ML, labs could be a lot better though, they lack proper explanations and don't cover some of the basics necessary to complete them.
Even are more basic knowledge of Trading and ML, still with specific data relative Trading and finance, Great!
Great introductory course to give you the taste of what lies ahead. Not a stand alone, as does not provide sufficient knowledge to build DNN on financial data.
Excellent! But, I am missing some of the prerequisites since I just wanted to take a chance and try things out, but feel like proceeding further might lead to some stumbling blocks.
About the Machine Learning for Trading Specialization

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